Recovery of Vegetation Canopy After Severe Fire in 2000 at the Black Hills National Forest, South Dakota, USA

Forest fires often result in varying degrees of canopy loss in forested landscapes. The subsequent trajectory of vegetation canopy recovery is important for ecosystem processes because the canopy controls photosynthesis and evapotranspiration. The loss and recovery of a canopy is often measured by leaf area index (LAI) and other vegetation indices that are related to canopy photosynthetic capacity. In this study we used time series imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite over the period of 2000–2009 to track the recovery of the vegetation canopy after fire. The Black Hills National Forest, South Dakota, USA experienced an extensive wildfire starting on August 24, 2000 that burned a total area of 33 785 ha, most of which was ponderosa pine forest. The MODIS data show that canopy photosynthetic capacity, as measured by LAI, recovered within 3 years (2001–2003). This recovery was attributed to rapid emergence of understory grass species after the fire event. Satellite-based Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) at the burned sites also recovered within 3 years (2001–2003). Rapid recovery of LAI, NDVI, and EVI at the burned sites makes it difficult to use these variables for identifying and mapping burned sites several years after the fire event. However, the Land Surface Water Index (LSWI), calculated as a normalized ratio between near infrared and shortwave infrared bands (band 2 and band 6 (1628–1652 nm) in MODIS sensor), was able to identify and track the burned sites over the entire period of 2000–2009. This finding opens a window of opportunity to identify and map disturbances using imagery from those sensors with both NIR and SWIR bands, including Landsat 5 TM (dating back to 1984); furthermore, a longer record of disturbance and recovery helps to improve our understanding of disturbance regimes, simulations of forest succession, and the carbon cycle.